Automatic road crack detection and analysis system based on deep feature fusion and edge structure extraction-Reference-Cited by-同舟云学术

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Automatic road crack detection and analysis system based on deep feature fusion and edge structure extraction

Published:2023-11-27 Issue:1 Volume:24 Page:
ISSN:1029-8436
Container-title:International Journal of Pavement Engineering
language:en
Short-container-title:International Journal of Pavement Engineering

Author:

Li Gang¹,Xin Yi²,Shen Dan³,Wang Biao¹,Deng Youwei²,Zhang Shengpeng²

Affiliation:

1. School of Energy and Electric Engineering, Chang’an University, Xi’an, People’s Republic of China

2. School of Electronics and Control Engineering, Chang’an University, Xi'an, People’s Republic of China

3. Security Department, Chang'an University, Xi'an, People’s Republic of China

Funder

the Key Research and Development Program Projects of Shaanxi

Key Research and Development Program of Shaanxi

the Key Research and Development Program of Guangxi

the Science and Technology Bureau of Xi’an project

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Civil and Structural Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/10298436.2023.2246096

Reference45 articles.

1. Structural crack detection using deep convolutional neural networks

2. Attention-based generative adversarial network with internal damage segmentation using thermography

3. Alom M. Z. et al . 2018. Recurrent residual convolutional neural network based on u-net (r2u-net) for medical image segmentation. arXiv preprint arXiv:1802.06955 .

4. Recurrent residual U-Net for medical image segmentation;Alom M. Z.;J Med Imaging (Bellingham),2019

5. SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

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